Three practical pieces of advice on preventing advanced analytics projects from failing

Advanced analytics involves solving complex business problems with organizational data that can bring out valuable insights. These insights capture the value that enterprises need in making critical business decisions. Unlocking the value of analytics has the potential to deliver numerous benefits and seize future opportunities.

We often see a stark contrast between expectations vs. reality that analytics projects provide. It happens due to several causes, including complications with user adoption and the inability of analytics teams to visualize the user's journey. A unity across multidisciplinary teams can resolve analytics failures and build a robust and resilient business.    

In this present article, our discussion will revolve around providing you with three essential tips and tricks that can prevent advanced analytics projects from failing. Let's dive right into discussing them;  

1.     BUILD A STRONG KNOWLEDGE AND INSIGHTS SHARING CULTURE  

One of the essential steps that teams can take is to build a culture of knowledge sharing in their organization. When teams across various disciplines share their respective insights and knowledge, they begin to solve similar problems from different angles. Having a knowledge-sharing culture will lead to moments of clarity where insights will shed light on new purposes of thinking, unique patterns, and priorities, all derived from data. This type of knowledge-sharing culture proves to be highly useful in aligning teams in a focused direction.   

2.     INTEGRATE ANALYTICS AND DESIGN TO UNDERSTAND THE END-USER JOURNEY BETTER  

A proactive role of designers from the start of the project will ensure a better model later. Designers can take data scientists through an enriching understanding of the user journey, which leads to a more excellent grasp of what the user expects from the tool and reduces cycle times in feature engineering. Consequently, collaboration among data scientists and designers can deliver a better model with improved features and predictors.   

3.     UTILIZE DESIGNER'S TOOLS; FUTURE STATE MAPPING IN ANALYTICS   

Designers often use future state mapping while developing interfaces. It is a standard tool that visualizes how a user progresses through the process. For a broader view, analytics teams can use this tool to understand and align with what the solution is generating for users with the end goal of how the solution is delivered to assist them in achieving their objectives. Another factor that might add value to the analytics projects is that this tool can help them reimagine processes that the user goes through, thus enhancing the model's functioning.   

Conclusion   

The present article took you as a reader on a journey of how analytics, despite being a powerful tool, struggles to reach its potential due to some factors that create obstacles. User adoption is the leading cause behind why analytics projects fail. To resolve such issues, we recommended using the designer's perspective and other teams' perspectives into account as they can help the technical team subdue the challenges and take them through the user's journey.    

 Another factor that comes to play is using designers' standard tools, i.e., future state mapping, to experience and visualize what end-users go through while using their delivered solutions. Not only does it help in aligning the entire team with a single objective, but it also promotes the mutual need for collaboration across multidisciplinary teams. Sharing knowledge and insights can solve similar problems simultaneously, saving time and energy for other projects.